Developing Tomorrow's Statisticians

Bryce, G. Rex

doi:10.1080/10691898.2005.11910636

Cited by 15 publications

(19 citation statements)

References 8 publications

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“…As a result, statistics educators, researchers and specialists are motivated to form communities and committees focusing on developing curriculum guidelines for college-level statistics education. For example, in 1999, the Undergraduate Statistics Education Initiative (USEI), a committee of ten representatives from academia, industry, and the government, began meeting to suggest improvements for the college statistics curriculum (Bryce, 2005). Additionally, in 2003, the American Statistical Association published a curricular guideline for college-level statistics.…”

Section: Challenges Of Integrating Technology Into Statistics Classroommentioning

confidence: 99%

“…Also, proficiency in statistical skills has been observed to improve job performance because the computational tasks are routinely performed in most professions. Due to the importance, statistics educators, researchers and specialists are motivated to develop curriculum guidelines and conduct related studies for collegelevel statistics education (Bryce, 2005; "Curriculum guidelines for undergraduate programs in statistical science," 2010; National council of teachers of Mathematics, 1989). The body of studies related to teaching and learning statistics is growing, however, many statistics teachers continue to express difficulty in helping students understand the course material (Garfield , 1995;Garfield & Ahlgren, 1988).…”

Section: Concept Development In Statisticsmentioning

confidence: 99%

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The impact of animation interactivity on novices’ learning of introductory statistics

Wang

Vaughn

Liu

2011

Computers & Education

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and their never-ending supports. This study was a one-way design where the independent variable was animation interactivity. In addition to a control group (Static Group) provided with only static materials, there were three groups with different levels of animation interactivity: 1) Animation with simple interactivity (Simple Animation Group), 2) animation with input vii manipulation (Input Group), and 3) animation with practice and feedback (Practice Group). A sample of 123 college students participated in the study and was randomly assigned into groups. They gathered in the computer lab to work with the animation program and then took online surveys and tests for evaluation. Students were expected to learn Principles of Hypothesis Testing (concepts of type I error, type II error and pvalue). The data collected in this study included 1) student learning attitudes, 2) achievement and confidence pre-test scores, 3) achievement and confidence post-test scores, and 4) program perception. Also, student manipulation of the animation program was recorded as Web log data. The data were analyzed by using multivariate analysis (MANOVA), univariate analysis (ANOVA), regression analysis, regression tree analysis and case analysis.The findings were as follows: 1) Animation interactivity impacted students' improvement in understanding (p=.006) and lower-level applying (p=.042), 2) animation interactivity did not impact student confidence and program perception, 3) the regression analysis indicated that student prior knowledge and interest were the most important predictors on student achievement post-test scores instead of program manipulation, and 4) the regression tree showed that there were interactions among student interest, prior knowledge, and program manipulation on the achievement post-test scores. The case analysis showed that not all students manipulated the interactive animation program as expected due to a lack of motivation and cognitive skills, and this could decrease the effect of the interactive animation. This study hoped to broaden theories on interactive learning and serve as a reference for future statistics curriculum designers and textbook publishers.viii He asked students to first clarify the definition of the type I and type II error, and then look for clues in the question for computation. The type I and type II error problems are difficult for most novice learners. But with the concrete examples of "bags," "boxes," List of Tablesor "envelopes," statistics was no longer as difficult for me. This particular teaching method is valuable for use in all introductory-level classes. 3I believe this struggle with learning statistics is not limited to myself, but is common to many other students. As a result, I created an online animated program based on my instructor's teaching method in order to help learners who also struggle with learning type I error, type II error and the p-value. This online animation was created to popularize this particular teaching method. To benefit learners with different ...

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Section: Challenges Of Integrating Technology Into Statistics Classroommentioning

confidence: 99%

Section: Concept Development In Statisticsmentioning

confidence: 99%

The impact of animation interactivity on novices’ learning of introductory statistics

Wang

Vaughn

Liu

2011

Computers & Education

View full text Add to dashboard Cite

show abstract

“…Passive learning 6 (Bryce 2005) may provide students with a 'recipe approach' to learning hypothesis testing, which can also be beneficial in providing students a structure to follow. However, enabling students to firstly tell the lecturer what is a sensible idea in hypothesis testing is a powerful and enriching procedure.…”

Section: The Philosophy Behind Hypothesis Testing and P-values -Diagrmentioning

confidence: 99%

“…It is contrasted to passive learning in which information is presented to students who are expected to absorb it through contemplation and memorization of notes and textbook material. Students can learn actively by working problems for themselves, thinking about concepts to form their own summaries and statements…" (Bryce 2005) 2 In the lecture it is useful to simply identify the lowest and highest values along the number line and place the crosses between them to ensure students are not being distracted by numbers. An interactive hand-drawn sketch in colour pen on an overhead transparency can aid the presentation, reducing the rigidity that may be felt if Figure 1 was typed up and pre-prepared for display in the class.…”

Section: Footnotesmentioning

confidence: 99%

“…The crux of such examples is to remove the mystery surrounding statistical concepts and techniques by enabling students to explain or define a concept themselves rather than simply being told the concept. The approach builds upon the concepts of "active learning" 1 (Bryce 2005)and "making it memorable" and "striking demonstrations" as theorised by Sowey (Sowey 1995(Sowey , 2001; having both similarities and differences to the latter. A third objective is to present novel examples of how to engage students and aid their recall of certain important aspects of a Statistics course.…”

Section: Introductionmentioning

confidence: 99%

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Keeping it Real, Keeping Them Interested and Keeping it in Their Minds

Howley

2008

Journal of Statistics Education

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As part of many universities' Business degrees, students will undertake an introductory statistics course. Lecturers need to help these students appreciate and recognise the value of possessing quantitative skills and to learn and apply such skills. Three components to teaching that address these aims as well as the interdependence of these components as part of a process which enhances the teaching environment and student outcomes are described. Methods and examples to perform the techniques and ideas are provided along with a discussion of their implementation and effectiveness after delivery in a large first year course.

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References

2011

A Career in Statistics

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Developing Tomorrow's Statisticians

Cited by 15 publications

References 8 publications

The impact of animation interactivity on novices’ learning of introductory statistics

The impact of animation interactivity on novices’ learning of introductory statistics

Keeping it Real, Keeping Them Interested and Keeping it in Their Minds

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